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Verdonk F, Cambriel A, Hedou J, Ganio E, Bellan G, Gaudilliere D, Einhaus J, Sabayev M, Stelzer IA, Feyaerts D, Bonham AT, Ando K, Choisy B, Drover D, Heifets B, Chretien F, Aghaeepour N, Angst MS, Molliex S, Sharshar T, Gaillard R, Gaudilliere B. An immune signature of postoperative cognitive decline in elderly patients. bioRxiv 2024:2024.03.02.582845. [PMID: 38496400 PMCID: PMC10942349 DOI: 10.1101/2024.03.02.582845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Postoperative cognitive decline (POCD) is the predominant complication affecting elderly patients following major surgery, yet its prediction and prevention remain challenging. Understanding biological processes underlying the pathogenesis of POCD is essential for identifying mechanistic biomarkers to advance diagnostics and therapeutics. This longitudinal study involving 26 elderly patients undergoing orthopedic surgery aimed to characterize the impact of peripheral immune cell responses to surgical trauma on POCD. Trajectory analyses of single-cell mass cytometry data highlighted early JAK/STAT signaling exacerbation and diminished MyD88 signaling post-surgery in patients who developed POCD. Further analyses integrating single-cell and plasma proteomic data collected before surgery with clinical variables yielded a sparse predictive model that accurately identified patients who would develop POCD (AUC = 0.80). The resulting POCD immune signature included one plasma protein and ten immune cell features, offering a concise list of biomarker candidates for developing point-of-care prognostic tests to personalize perioperative management of at-risk patients. The code and the data are documented and available at https://github.com/gregbellan/POCD . Teaser Modeling immune cell responses and plasma proteomic data predicts postoperative cognitive decline.
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Cambriel A, Choisy B, Hedou J, Bonnet MP, Fellous S, Lefevre JH, Voron T, Gaudillière D, Kin C, Gaudillière B, Verdonk F. Impact of preoperative uni- or multimodal prehabilitation on postoperative morbidity: meta-analysis. BJS Open 2023; 7:zrad129. [PMID: 38108466 PMCID: PMC10726416 DOI: 10.1093/bjsopen/zrad129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 10/03/2023] [Accepted: 10/19/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND Postoperative complications occur in up to 43% of patients after surgery, resulting in increased morbidity and economic burden. Prehabilitation has the potential to increase patients' preoperative health status and thereby improve postoperative outcomes. However, reported results of prehabilitation are contradictory. The objective of this systematic review is to evaluate the effects of prehabilitation on postoperative outcomes (postoperative complications, hospital length of stay, pain at postoperative day 1) in patients undergoing elective surgery. METHODS The authors performed a systematic review and meta-analysis of RCTs published between January 2006 and June 2023 comparing prehabilitation programmes lasting ≥14 days to 'standard of care' (SOC) and reporting postoperative complications according to the Clavien-Dindo classification. Database searches were conducted in PubMed, CINAHL, EMBASE, PsycINFO. The primary outcome examined was the effect of uni- or multimodal prehabilitation on 30-day complications. Secondary outcomes were length of ICU and hospital stay (LOS) and reported pain scores. RESULTS Twenty-five studies (including 2090 patients randomized in a 1:1 ratio) met the inclusion criteria. Average methodological study quality was moderate. There was no difference between prehabilitation and SOC groups in regard to occurrence of postoperative complications (OR = 1.02, 95% c.i. 0.93 to 1.13; P = 0.10; I2 = 34%), total hospital LOS (-0.13 days; 95% c.i. -0.56 to 0.28; P = 0.53; I2 = 21%) or reported postoperative pain. The ICU LOS was significantly shorter in the prehabilitation group (-0.57 days; 95% c.i. -1.10 to -0.04; P = 0.03; I2 = 46%). Separate comparison of uni- and multimodal prehabilitation showed no difference for either intervention. CONCLUSION Prehabilitation reduces ICU LOS compared with SOC in elective surgery patients but has no effect on overall complication rates or total LOS, regardless of modality. Prehabilitation programs need standardization and specific targeting of those patients most likely to benefit.
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Affiliation(s)
- Amélie Cambriel
- Department of Anesthesiology and Intensive Care, Hôpital Saint-Antoine, Assistance Publique-Hôpitaux de Paris, Paris, France
- GRC 29, DMU DREAM, Sorbonne University, Assistance Publique-Hôpitaux de Paris, Paris, France
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Julien Hedou
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Marie-Pierre Bonnet
- GRC 29, DMU DREAM, Sorbonne University, Assistance Publique-Hôpitaux de Paris, Paris, France
- Department of Anesthesia and Critical Care, Trousseau Hospital, Assistance Publique-Hôpitaux de Paris, Sorbonne University, Paris, France
- Obstetrical Perinatal and Paediatric Epidemiology Research Team, Université Paris Cité, CRESS, EPOPé, INSERM, INRA, Paris, France
| | - Souad Fellous
- Department of Anesthesiology and Intensive Care, Hôpital Saint-Antoine, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Jérémie H Lefevre
- Sorbonne University and Department of Digestive Surgery, Hôpital Saint-Antoine, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Thibault Voron
- Sorbonne University and Department of Digestive Surgery, Hôpital Saint-Antoine, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Dyani Gaudillière
- Division of Plastic & Reconstructive Surgery, Department of Surgery, Stanford University, Stanford, California, USA
| | - Cindy Kin
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, California, USA
| | - Brice Gaudillière
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Franck Verdonk
- Department of Anesthesiology and Intensive Care, Hôpital Saint-Antoine, Assistance Publique-Hôpitaux de Paris, Paris, France
- GRC 29, DMU DREAM, Sorbonne University, Assistance Publique-Hôpitaux de Paris, Paris, France
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
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Rumer KK, Hedou J, Tsai A, Einhaus J, Verdonk F, Stanley N, Choisy B, Ganio E, Bonham A, Jacobsen D, Warrington B, Gao X, Tingle M, McAllister TN, Fallahzadeh R, Feyaerts D, Stelzer I, Gaudilliere D, Ando K, Shelton A, Morris A, Kebebew E, Aghaeepour N, Kin C, Angst MS, Gaudilliere B. Integrated Single-cell and Plasma Proteomic Modeling to Predict Surgical Site Complications: A Prospective Cohort Study. Ann Surg 2022; 275:582-590. [PMID: 34954754 PMCID: PMC8816871 DOI: 10.1097/sla.0000000000005348] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of this study was to determine whether single-cell and plasma proteomic elements of the host's immune response to surgery accurately identify patients who develop a surgical site complication (SSC) after major abdominal surgery. SUMMARY BACKGROUND DATA SSCs may occur in up to 25% of patients undergoing bowel resection, resulting in significant morbidity and economic burden. However, the accurate prediction of SSCs remains clinically challenging. Leveraging high-content proteomic technologies to comprehensively profile patients' immune response to surgery is a promising approach to identify predictive biological factors of SSCs. METHODS Forty-one patients undergoing non-cancer bowel resection were prospectively enrolled. Blood samples collected before surgery and on postoperative day one (POD1) were analyzed using a combination of single-cell mass cytometry and plasma proteomics. The primary outcome was the occurrence of an SSC, including surgical site infection, anastomotic leak, or wound dehiscence within 30 days of surgery. RESULTS A multiomic model integrating the single-cell and plasma proteomic data collected on POD1 accurately differentiated patients with (n = 11) and without (n = 30) an SSC [area under the curve (AUC) = 0.86]. Model features included coregulated proinflammatory (eg, IL-6- and MyD88- signaling responses in myeloid cells) and immunosuppressive (eg, JAK/STAT signaling responses in M-MDSCs and Tregs) events preceding an SSC. Importantly, analysis of the immunological data obtained before surgery also yielded a model accurately predicting SSCs (AUC = 0.82). CONCLUSIONS The multiomic analysis of patients' immune response after surgery and immune state before surgery revealed systemic immune signatures preceding the development of SSCs. Our results suggest that integrating immunological data in perioperative risk assessment paradigms is a plausible strategy to guide individualized clinical care.
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Affiliation(s)
- Kristen K. Rumer
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Julien Hedou
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Amy Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Jakob Einhaus
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
- Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University of Tuebingen, Tuebingen, Germany
| | - Franck Verdonk
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
- Sorbonne University, GRC 29, DMU DREAM, Assistance Publique-Hôpitaux de Paris, France
| | - Natalie Stanley
- Department of Computer Science and Computational Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Edward Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Adam Bonham
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Danielle Jacobsen
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Beata Warrington
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Xiaoxiao Gao
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Martha Tingle
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Tiffany N. McAllister
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Ramin Fallahzadeh
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Dorien Feyaerts
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Ina Stelzer
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Dyani Gaudilliere
- Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Kazuo Ando
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Andrew Shelton
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Arden Morris
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Electron Kebebew
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
- Department of Biomedical Data Sciences, Stanford University, Stanford, CA
- Department of Pediatrics, Stanford University, Stanford, CA
| | - Cindy Kin
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Martin S. Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
- Department of Pediatrics, Stanford University, Stanford, CA
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4
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Verdonk F, Einhaus J, Tsai AS, Hedou J, Choisy B, Gaudilliere D, Kin C, Aghaeepour N, Angst MS, Gaudilliere B. Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes. Curr Opin Crit Care 2021; 27:717-725. [PMID: 34545029 PMCID: PMC8585713 DOI: 10.1097/mcc.0000000000000883] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
PURPOSE OF REVIEW Postoperative complications including infections, cognitive impairment, and protracted recovery occur in one-third of the 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on our healthcare system. However, the accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain as major clinical challenges. RECENT FINDINGS Although multifactorial in origin, the dysregulation of immunological mechanisms that occur in response to surgical trauma is a key determinant of postoperative complications. Prior research, primarily focusing on inflammatory plasma markers, has provided important clues regarding their pathogenesis. However, the recent advent of high-content, single-cell transcriptomic, and proteomic technologies has considerably improved our ability to characterize the immune response to surgery, thereby providing new means to understand the immunological basis of postoperative complications and to identify prognostic biological signatures. SUMMARY The comprehensive and single-cell characterization of the human immune response to surgery has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers, ultimately providing patients and surgeons with actionable information to improve surgical outcomes. Although recent studies have generated a wealth of knowledge, laying the foundation for a single-cell atlas of the human immune response to surgery, larger-scale multiomic studies are required to derive robust, scalable, and sufficiently powerful models to accurately predict the risk of postoperative complications in individual patients.
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Affiliation(s)
- Franck Verdonk
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine
| | - Jakob Einhaus
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine
| | - Amy S Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine
| | - Julien Hedou
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine
| | | | - Cindy Kin
- Department of Surgery, Stanford University School of Medicine
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine
- Department of Biomedical Data Science, Stanford University
- Department of Pediatrics, Stanford University, Stanford, California, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine
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5
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Stelzer IA, Ghaemi MS, Han X, Ando K, Hédou JJ, Feyaerts D, Peterson LS, Rumer KK, Tsai ES, Ganio EA, Gaudillière DK, Tsai AS, Choisy B, Gaigne LP, Verdonk F, Jacobsen D, Gavasso S, Traber GM, Ellenberger M, Stanley N, Becker M, Culos A, Fallahzadeh R, Wong RJ, Darmstadt GL, Druzin ML, Winn VD, Gibbs RS, Ling XB, Sylvester K, Carvalho B, Snyder MP, Shaw GM, Stevenson DK, Contrepois K, Angst MS, Aghaeepour N, Gaudillière B. Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset. Sci Transl Med 2021; 13:13/592/eabd9898. [PMID: 33952678 DOI: 10.1126/scitranslmed.abd9898] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 12/01/2020] [Accepted: 04/14/2021] [Indexed: 12/28/2022]
Abstract
Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10-40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10-7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies.
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Affiliation(s)
- Ina A Stelzer
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Mohammad S Ghaemi
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Digital Technologies Research Centre, National Research Council Canada, Toronto, ON M5T 3J1, Canada
| | - Xiaoyuan Han
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Department of Biomedical Sciences, University of the Pacific, Arthur A. Dugoni School of Dentistry, San Francisco, CA 94103, USA
| | - Kazuo Ando
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Julien J Hédou
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Dorien Feyaerts
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Laura S Peterson
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Kristen K Rumer
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Eileen S Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Edward A Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Dyani K Gaudillière
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Amy S Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Lea P Gaigne
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Franck Verdonk
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Danielle Jacobsen
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Sonia Gavasso
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Department of Neurology, NeuroSys-Med, Haukeland University Hospital, 5021 Bergen, Norway
| | - Gavin M Traber
- Department of Genetics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Mathew Ellenberger
- Department of Genetics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Natalie Stanley
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Martin Becker
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Ramin Fallahzadeh
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Ronald J Wong
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Gary L Darmstadt
- Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Maurice L Druzin
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Virginia D Winn
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Ronald S Gibbs
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Xuefeng B Ling
- Department of Surgery, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Karl Sylvester
- Department of Surgery, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Brendan Carvalho
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Gary M Shaw
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - David K Stevenson
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA.,Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Brice Gaudillière
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA 94305, USA. .,Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA 94305, USA
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6
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Ganio EA, Stanley N, Lindberg-Larsen V, Einhaus J, Tsai AS, Verdonk F, Culos A, Ghaemi S, Rumer KK, Stelzer IA, Gaudilliere D, Tsai E, Fallahzadeh R, Choisy B, Kehlet H, Aghaeepour N, Angst MS, Gaudilliere B. Author Correction: Preferential inhibition of adaptive immune system dynamics by glucocorticoids in patients after acute surgical trauma. Nat Commun 2020; 11:4495. [PMID: 32883978 PMCID: PMC7471263 DOI: 10.1038/s41467-020-18410-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- Edward A Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Natalie Stanley
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Jakob Einhaus
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Amy S Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Franck Verdonk
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Sajjad Ghaemi
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA.,Digital Technologies Research Centre, National Research Council Canada, Toronto, ON, Canada
| | - Kristen K Rumer
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Ina A Stelzer
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Dyani Gaudilliere
- Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA, USA
| | - Eileen Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Ramin Fallahzadeh
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Henrik Kehlet
- Section of Surgical Pathophysiology 7621, Rigshospitalet, Blegdamsvej 9, DK-2100, Copenhagen, Denmark
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA.
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7
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Ganio EA, Stanley N, Lindberg-Larsen V, Einhaus J, Tsai AS, Verdonk F, Culos A, Ghaemi S, Rumer KK, Stelzer IA, Gaudilliere D, Tsai E, Fallahzadeh R, Choisy B, Kehlet H, Aghaeepour N, Angst MS, Gaudilliere B. Preferential inhibition of adaptive immune system dynamics by glucocorticoids in patients after acute surgical trauma. Nat Commun 2020; 11:3737. [PMID: 32719355 PMCID: PMC7385146 DOI: 10.1038/s41467-020-17565-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 07/03/2020] [Indexed: 02/08/2023] Open
Abstract
Glucocorticoids (GC) are a controversial yet commonly used intervention in the clinical management of acute inflammatory conditions, including sepsis or traumatic injury. In the context of major trauma such as surgery, concerns have been raised regarding adverse effects from GC, thereby necessitating a better understanding of how GCs modulate the immune response. Here we report the results of a randomized controlled trial (NCT02542592) in which we employ a high-dimensional mass cytometry approach to characterize innate and adaptive cell signaling dynamics after a major surgery (primary outcome) in patients treated with placebo or methylprednisolone (MP). A robust, unsupervised bootstrap clustering of immune cell subsets coupled with random forest analysis shows profound (AUC = 0.92, p-value = 3.16E-8) MP-induced alterations of immune cell signaling trajectories, particularly in the adaptive compartments. By contrast, key innate signaling responses previously associated with pain and functional recovery after surgery, including STAT3 and CREB phosphorylation, are not affected by MP. These results imply cell-specific and pathway-specific effects of GCs, and also prompt future studies to examine GCs' effects on clinical outcomes likely dependent on functional adaptive immune responses.
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Affiliation(s)
- Edward A Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Natalie Stanley
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Jakob Einhaus
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Amy S Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Franck Verdonk
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Sajjad Ghaemi
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
- Digital Technologies Research Centre, National Research Council Canada, Toronto, ON, Canada
| | - Kristen K Rumer
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Ina A Stelzer
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Dyani Gaudilliere
- Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA, USA
| | - Eileen Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Ramin Fallahzadeh
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Henrik Kehlet
- Section of Surgical Pathophysiology 7621, Rigshospitalet, Blegdamsvej 9, DK-2100, Copenhagen, Denmark
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA.
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8
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Tsai AS, Berry K, Beneyto MM, Gaudilliere D, Ganio EA, Culos A, Ghaemi MS, Choisy B, Djebali K, Einhaus JF, Bertrand B, Tanada A, Stanley N, Fallahzadeh R, Baca Q, Quach LN, Osborn E, Drag L, Lansberg MG, Angst MS, Gaudilliere B, Buckwalter MS, Aghaeepour N. A year-long immune profile of the systemic response in acute stroke survivors. Brain 2019; 142:978-991. [PMID: 30860258 DOI: 10.1093/brain/awz022] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2018] [Revised: 11/18/2018] [Accepted: 12/14/2018] [Indexed: 02/07/2023] Open
Abstract
Stroke is a leading cause of cognitive impairment and dementia, but the mechanisms that underlie post-stroke cognitive decline are not well understood. Stroke produces profound local and systemic immune responses that engage all major innate and adaptive immune compartments. However, whether the systemic immune response to stroke contributes to long-term disability remains ill-defined. We used a single-cell mass cytometry approach to comprehensively and functionally characterize the systemic immune response to stroke in longitudinal blood samples from 24 patients over the course of 1 year and correlated the immune response with changes in cognitive functioning between 90 and 365 days post-stroke. Using elastic net regularized regression modelling, we identified key elements of a robust and prolonged systemic immune response to ischaemic stroke that occurs in three phases: an acute phase (Day 2) characterized by increased signal transducer and activator of transcription 3 (STAT3) signalling responses in innate immune cell types, an intermediate phase (Day 5) characterized by increased cAMP response element-binding protein (CREB) signalling responses in adaptive immune cell types, and a late phase (Day 90) by persistent elevation of neutrophils, and immunoglobulin M+ (IgM+) B cells. By Day 365 there was no detectable difference between these samples and those from an age- and gender-matched patient cohort without stroke. When regressed against the change in the Montreal Cognitive Assessment scores between Days 90 and 365 after stroke, the acute inflammatory phase Elastic Net model correlated with post-stroke cognitive trajectories (r = -0.692, Bonferroni-corrected P = 0.039). The results demonstrate the utility of a deep immune profiling approach with mass cytometry for the identification of clinically relevant immune correlates of long-term cognitive trajectories.
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Affiliation(s)
- Amy S Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Kacey Berry
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Maxime M Beneyto
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Dyani Gaudilliere
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford School of Medicine, CA, USA
| | - Edward A Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Mohammad S Ghaemi
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Karim Djebali
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Jakob F Einhaus
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Basile Bertrand
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Athena Tanada
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Natalie Stanley
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Ramin Fallahzadeh
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Quentin Baca
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Lisa N Quach
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Elizabeth Osborn
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Lauren Drag
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Maarten G Lansberg
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Marion S Buckwalter
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA.,Department of Neurosurgery, Stanford School of Medicine, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
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9
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Gaudilliere DK, Culos A, Djebali K, Tsai AS, Ganio EA, Choi WM, Han X, Maghaireh A, Choisy B, Baca Q, Einhaus JF, Hedou JJ, Bertrand B, Ando K, Fallahzadeh R, Ghaemi MS, Okada R, Stanley N, Tanada A, Tingle M, Alpagot T, Helms JA, Angst MS, Aghaeepour N, Gaudilliere B. Systemic Immunologic Consequences of Chronic Periodontitis. J Dent Res 2019; 98:985-993. [PMID: 31226001 DOI: 10.1177/0022034519857714] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Chronic periodontitis (ChP) is a prevalent inflammatory disease affecting 46% of the US population. ChP produces a profound local inflammatory response to dysbiotic oral microbiota that leads to destruction of alveolar bone and tooth loss. ChP is also associated with systemic illnesses, including cardiovascular diseases, malignancies, and adverse pregnancy outcomes. However, the mechanisms underlying these adverse health outcomes are poorly understood. In this prospective cohort study, we used a highly multiplex mass cytometry immunoassay to perform an in-depth analysis of the systemic consequences of ChP in patients before (n = 28) and after (n = 16) periodontal treatment. A high-dimensional analysis of intracellular signaling networks revealed immune system-wide dysfunctions differentiating patients with ChP from healthy controls. Notably, we observed exaggerated proinflammatory responses to Porphyromonas gingivalis-derived lipopolysaccharide in circulating neutrophils and monocytes from patients with ChP. Simultaneously, natural killer cell responses to inflammatory cytokines were attenuated. Importantly, the immune alterations associated with ChP were no longer detectable 3 wk after periodontal treatment. Our findings demarcate systemic and cell-specific immune dysfunctions in patients with ChP, which can be temporarily reversed by the local treatment of ChP. Future studies in larger cohorts are needed to test the boundaries of generalizability of our results.
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Affiliation(s)
- D K Gaudilliere
- 1 Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA, USA
| | - A Culos
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - K Djebali
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - A S Tsai
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - E A Ganio
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - W M Choi
- 1 Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA, USA
| | - X Han
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - A Maghaireh
- 1 Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA, USA
| | - B Choisy
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Q Baca
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - J F Einhaus
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - J J Hedou
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - B Bertrand
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - K Ando
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - R Fallahzadeh
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - M S Ghaemi
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - R Okada
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - N Stanley
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - A Tanada
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - M Tingle
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - T Alpagot
- 3 Department of Periodontics, Arthur A. Dugoni School of Dentistry, University of the Pacific, San Francisco, CA, USA
| | - J A Helms
- 1 Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA, USA
| | - M S Angst
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - N Aghaeepour
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - B Gaudilliere
- 2 Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA, USA
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10
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Tsai AS, Berry K, Beneyto MM, Gaudilliere D, Ganio EA, Choisy B, Djebali K, Baca Q, Quach L, Drag L, Lansberg MG, Angst MS, Gaudilliere B, Buckwalter MS, Aghaeepour N. Abstract WP564: Deep Immune Profiling of the Post-Stroke Peripheral Immune Response Reveals Tri-phasic Response and Correlations With Long-Term Cognitive Outcomes. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.wp564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
Stroke produces profound local and systemic immune responses that engage all major innate and adaptive immune compartments. The aim of this study was to characterize the systemic immune response to stroke and to determine if it contributes to long-term cognitive disability.
Methods:
We included 24 consecutive subjects with ischemic stroke and excluded patients for autoimmune disorders, use of immunosuppressant drugs, or life expectancy <90 days. Blood samples were collected for up to 9 timepoints after stroke (days 1, 2, 3, 5, 7, 14, 30, 90, and 365). Change in cognitive function between days 90 and 365 was assessed using the Montreal Cognitive Assessment (MoCA). Control samples were from a cohort of 24 sex- and age-matched patients prior to hip replacement surgery. We used mass cytometry to acquire 240 immune features from each sample, representing 20 immune cell subtypes, their frequency, cell surface markers, and activation states. Elastic Net (EN) regularized regression modeling was used to characterize phases of the immune response and to correlate stages of the immune response with change in cognitive function.
Results:
The EN model identified three distinct phases of the systemic immune response to ischemic stroke: The acute phase (day 2) was characterized by increased STAT3 (signal transducer and activator of transcription 3) signaling responses in innate immune cell types. The intermediate phase (day 5) was characterized by increased CREB (cAMP response element-binding protein) signaling responses in adaptive immune cell types. The late phase (day 90) was characterized by persistent elevation of neutrophils and IgM+ B cells. By day 365 there was a return to baseline immune responses, comparable to the controls. A decline in MoCA scores between day 90 and day 365 after stroke correlated with a stronger inflammatory response in the acute phase (r = -0.692, Bonferroni-corrected p = 0.04).
Conclusions:
The results demonstrate three distinct phases of the peripheral immune response that occur after stroke, spanning from days 2 to day 90. The acute phase immune response predicts post-stroke cognitive decline, suggesting that therapies aimed at optimizing this response could lead to preservation of cognitive functioning post-stroke.
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Affiliation(s)
- Amy S Tsai
- Anesthesiology, Stanford Med Sch, Stanford, CA
| | - Ketura Berry
- Neurology and Neurological Sciences, and Neurosurgery, Stanford Med Sch, Stanford, CA
| | | | | | | | | | | | | | - Lisa Quach
- Neurology and Neurological Sciences, and Neurosurgery, Stanford Med Sch, Stanford, CA
| | - Lauren Drag
- Neurology and Neurological Sciences, and Neurosurgery, Stanford Med Sch, Stanford, CA
| | - Maarten G Lansberg
- Neurology and Neurological Sciences, and Neurosurgery, Stanford Med Sch, Stanford, CA
| | | | | | - Marion S Buckwalter
- Neurology and Neurological Sciences, and Neurosurgery, Stanford Med Sch, Stanford, CA
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11
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Aghaeepour N, Kin C, Ganio EA, Jensen KP, Gaudilliere DK, Tingle M, Tsai A, Lancero HL, Choisy B, McNeil LS, Okada R, Shelton AA, Nolan GP, Angst MS, Gaudilliere BL. Deep Immune Profiling of an Arginine-Enriched Nutritional Intervention in Patients Undergoing Surgery. J Immunol 2017; 199:ji1700421. [PMID: 28794234 PMCID: PMC5807249 DOI: 10.4049/jimmunol.1700421] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 07/11/2017] [Indexed: 01/08/2023]
Abstract
Application of high-content immune profiling technologies has enormous potential to advance medicine. Whether these technologies reveal pertinent biology when implemented in interventional clinical trials is an important question. The beneficial effects of preoperative arginine-enriched dietary supplements (AES) are highly context specific, as they reduce infection rates in elective surgery, but possibly increase morbidity in critically ill patients. This study combined single-cell mass cytometry with the multiplex analysis of relevant plasma cytokines to comprehensively profile the immune-modifying effects of this much-debated intervention in patients undergoing surgery. An elastic net algorithm applied to the high-dimensional mass cytometry dataset identified a cross-validated model consisting of 20 interrelated immune features that separated patients assigned to AES from controls. The model revealed wide-ranging effects of AES on innate and adaptive immune compartments. Notably, AES increased STAT1 and STAT3 signaling responses in lymphoid cell subsets after surgery, consistent with enhanced adaptive mechanisms that may protect against postsurgical infection. Unexpectedly, AES also increased ERK and P38 MAPK signaling responses in monocytic myeloid-derived suppressor cells, which was paired with their pronounced expansion. These results provide novel mechanistic arguments as to why AES may exert context-specific beneficial or adverse effects in patients with critical illness. This study lays out an analytical framework to distill high-dimensional datasets gathered in an interventional clinical trial into a fairly simple model that converges with known biology and provides insight into novel and clinically relevant cellular mechanisms.
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Affiliation(s)
- Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Cindy Kin
- Department of Surgery, Stanford University School of Medicine, Stanford, CA 94121
| | - Edward A Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Kent P Jensen
- Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94121; and
| | - Dyani K Gaudilliere
- Department of Surgery, Stanford University School of Medicine, Stanford, CA 94121
| | - Martha Tingle
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Amy Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Hope L Lancero
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Leslie S McNeil
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Robin Okada
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Andrew A Shelton
- Department of Surgery, Stanford University School of Medicine, Stanford, CA 94121
| | - Garry P Nolan
- Department of Microbiology and Immunology, Stanford University, Stanford, CA 94121
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Brice L Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121;
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